From time immemorial there was a need to recognize and diagnose substances or objects to identify if they have been tampered with or adulterated. Immediate and precise identification of objects under examination are configured to recognize defects, forgery or diseases in the substances.
For example in the agriculture field there is a constantly need to recognize defects and diseases of agriculture products like fruits and vegetable, and more commonly in products such as milk, juice etc.
For example Mastitis, inflammation of the mammary glands of dairy cows, remains one of the costliest diseases in cattle and its early detection remains a major goal of the dairy industry. It has been established that currently available commercial devices do not appear to be sensitive enough to detect mastitis accurately on-line. The prior art solutions that are currently used to detect mastitis are based on the fact that mastitis causes changes in the conductivity of milk, by damaging the mammary membrane leading to alteration of the balance of sodium, potassium and chloride ions. Previous studies have demonstrated that these changes in milk conductivity can be used as a direct indicator of the presence and degree of mastitis infection.
In the past, the herd person usually noticed the appearance of the first clinical symptoms of mastitis on the animal. Nowadays, the detection of abnormal milk is required before milking according to the EU directive: “Before milking of the individual cow, the milker must inspect the appearance of the milk. If any physical abnormality is detected, milk from the cow must be withheld from delivery to the dairy”. Therefore, foremilk of each animal is now visually examined directly in the parlour using a strip cup or a plate. However, as no symptoms are really obvious, farmers or herdspersons rarely identify the primary signs during a routine inspection or during milking in individual cows. Hence, the biochemical properties of milk turn out to be very useful in order to evaluate the cow's metabolic status, in particular, the udder condition. In the last few decades, a variety of cow side tests and laboratory tests have been developed for detecting mastitis such as the strip cup test, the California Mastitis Test, etc. Thanks to these methods of detection, foremilk control is usually followed by owners of small herds, but it takes a lot of time and money for large herds.
Currently available in-line mastitis detectors are fitted to the long milk tube. They have a wire mesh filter through which milk passes. Mastitis clots clog the filter and clot-free milk is able to pass through the filter.
A variety of diagnostic tests for mastitis are available and are used as indicators of udder inflammation. They cannot, however, assess the degree of infection accurately. As the name indicates they are performed directly on the animal. These experiments are useful to indicate suspect samples but they cannot be accepted as definitive procedures as many false positives cases remain.
One of the solutions to overcome such problems, are described in the prior art, for example, in an article entitled “DESIGN AND DEVELOPMENT OF A NOVEL ELECTRONIC SENSOR FOR DETECTING MASTITIS BASED ON CONDUCTANCE/IMPEDANCE MEASUREMENTS” by Valerie FAVRY, another article relating to adulteration detection entitled “Microwave Reflectometry Based Electrical Characterization of Milk for Adulteration Detection” by Pallavi R. Malamel, Tapas K. Bhuiya and Rajiv K. Gupta.
Other fields where a substance diagnose process is required may be for example to examine a spillage found in proximity to a water, gasoline or oil pipeline or tank as a good indication of the severity of water or gasoline leakage in a distribution network.
There are various techniques reported in the literature for leak detection such as a) Acoustic leak detection methods utilizing devices such as aquaphones or geophones to listen for leaks on the ground above the pipes b) acoustic correlation methods c) infrared thermography, tracer gas technique and ground-penetrating radar (GPR) d) Magnetic Flux Leakage (MFL) based detectors ultrasound (UT) to search for pipe defects.